{"id":"W2021086301","doi":"10.2135/cropsci2014.03.0203","title":"Mega‐environment Analysis and Test Location Evaluation Based on Unbalanced Multiyear Data","year":2014,"lang":"en","type":"article","venue":"Crop Science","topic":"Genetics and Plant Breeding","field":"Agricultural and Biological Sciences","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Biplot; Variety (cybernetics); Statistics; Mega-; Computer science; Biology; Data mining; Mathematics; Genotype; Genetics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01271301,0.0005856507,0.001081375,0.003052215,0.000628214,0.001294243,0.001132627,0.0003713439,0.004241215],"category_scores_gemma":[0.03282181,0.0003791459,0.001390726,0.003571814,0.0005357169,0.0009423883,0.001613921,0.001035377,0.0005103477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001186721,"about_ca_system_score_gemma":0.0008866523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007143445,"about_ca_topic_score_gemma":0.01276459,"domain_scores_codex":[0.9873554,0.009126041,0.0006113364,0.001138112,0.001386117,0.0003829873],"domain_scores_gemma":[0.9598358,0.0255371,0.003363285,0.005383903,0.005130942,0.0007488922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005679342,0.0006714448,0.4208139,0.0006268606,0.002325282,0.0011246,0.001963207,0.1498536,0.03002252,0.01410666,0.01253341,0.3602792],"study_design_scores_gemma":[0.0003240863,0.001874794,0.4869037,0.00007826435,0.0004839302,0.0002908597,0.001557853,0.4656839,0.01533201,0.007854592,0.01938146,0.0002345875],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5731567,0.0001301119,0.4115225,0.0001353664,0.00007167867,0.000642481,0.00767967,0.002917198,0.003744288],"genre_scores_gemma":[0.727627,0.00004015265,0.2635589,0.00003452572,0.00001214656,0.0006844238,0.006627399,0.0004175595,0.0009978794],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01271301,"threshold_uncertainty_score":0.06723356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05568089528776104,"score_gpt":0.2489252226860636,"score_spread":0.1932443273983026,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}